Receptor rigidity and ligand mobility in trypsin-ligand complexes

Exploring ligand dynamics in protein crystal structures with ensemble refinement

Understanding the dynamics of ligands bound to proteins is an important task in medicinal chemistry and drug design. However, the dominant technique for determining protein-ligand structures, X-ray crystallography, does not fully account for dynamics and cannot accurately describe the movements of ligands in protein binding sites. In this article, an alternative method, ensemble refinement, is used on six protein-ligand complexes with the aim of understanding the conformational diversity of ligands in protein crystal structures. The results show that ensemble refinement sometimes indicates that the flexibility of parts of the ligand and some protein side chains is larger than that which can be described by a single conformation and atomic displacement parameters. However, since the electron-density maps are comparable and Rfree values are slightly increased, the original crystal structure is still a better model from a statistical point of view. On the other hand, it is shown that molecular-dynamics simulations and automatic generation of alternative conformations in crystallographic refinement confirm that the flexibility of these groups is larger than is observed in standard refinement. Moreover, the flexible groups in ensemble refinement coincide with groups that give high atomic displacement parameters or non-unity occupancy if optimized in standard refinement. Therefore, the conformational diversity indicated by ensemble refinement seems to be qualitatively correct, indicating that ensemble refinement can be an important complement to standard crystallographic refinement as a tool to discover which parts of crystal structures may show extensive flexibility and therefore are poorly described by a single conformation. However, the diversity of the ensembles is often exaggerated (probably partly owing to the rather poor force field employed) and the ensembles should not be trusted in detail.

Water access and ligand dissociation at the binding site of proteins

Although water is undoubtedly an essential mediator of protein-ligand interactions, whether or not such water molecules are critical for the progress of ligand dissociation remains unclear. To gain a more complete understanding, molecular dynamics simulations are performed with two molecular systems, rigid model binding sites and trypsin-benzamidine. Free-energy landscapes are calculated with a suitably chosen solvent coordinate, which well describes water access to the ligand binding site. The results of free energy provided clear description of water-ligand exchange process, where two different mechanisms appear depending on whether the binding site is buried or not. As the site is more buried, water access is more difficult. When water does not access the site, ligand dissociation produces a large energy barrier, i.e., slow dissociation kinetics. This indicates that control of ligand dissociation kinetics becomes possible with burying the binding site. However, the results also showed that appropriate burying is important because burying reduces not only water access but also ligand binding. The role of the protein structural change is also discussed; it likely plays a similar role to water access because during ligand dissociation, it can make new coordination with the ligand binding site like water. These results contribute to the future pharmaceutical drug design and will be useful for fundamental exploration of various molecular events.

Adaptive simulations, towards interactive protein-ligand modeling

Modeling the dynamic nature of protein-ligand binding with atomistic simulations is one of the main challenges in computational biophysics, with important implications in the drug design process. Although in the past few years hardware and software advances have significantly revamped the use of molecular simulations, we still lack a fast and accurate ab initio description of the binding mechanism in complex systems, available only for up-to-date techniques and requiring several hours or days of heavy computation. Such delay is one of the main limiting factors for a larger penetration of protein dynamics modeling in the pharmaceutical industry. Here we present a game-changing technology, opening up the way for fast reliable simulations of protein dynamics by combining an adaptive reinforcement learning procedure with Monte Carlo sampling in the frame of modern multi-core computational resources. We show remarkable performance in mapping the protein-ligand energy landscape, being able to reproduce the full binding mechanism in less than half an hour, or the active site induced fit in less than 5 minutes. We exemplify our method by studying diverse complex targets, including nuclear hormone receptors and GPCRs, demonstrating the potential of using the new adaptive technique in screening and lead optimization studies.

Atomic-scale investigation of the interactions between tetrabromobisphenol A, tetrabromobisphenol S and bovine trypsin by spectroscopies and molecular dynamics simulations

Tetrabromobisphenol A (TBBPA) and its replacement alternative tetrabromobisphenol S (TBBPS) are used widely as brominated flame retardants (BFRs). However, the potential risk of their effects on bovine trypsin remains largely unknown. We investigated the effects of TBBPA and TBBPS to bovine trypsin by the fluorescence spectroscopy, circular dichroism and molecular dynamics (MD) simulations. They statically quenched the intrinsic fluorescence of bovine trypsin in a concentration-dependent mode and caused slight red-shifted fluorescence. The short and long fluorescence lifetime decay components of bovine trypsin were both affected, partly due to the disturbed microenvironmental changes of Trp215. The β-sheet content of bovine trypsin was significantly reduced from 82.4% to 75.7% and 76.6% by TBBPA and TBBPS, respectively, possibly impairing the physiological function of bovine trypsin. TBBPA and TBBPS bind at the 8-anilinonaphthalene-1-sulfonate (ANS) binding site with an association constant of 1.09×10(4) M(-1) and 2.41×10(4) M(-1) at 298 K, respectively. MD simulations revealed that van der Waals interactions and hydrogen bond interactions are dominant for TBBPA, whereas electrostatic interactions are critical for TBBPS. Our in vitro and in silico studies are beneficial to the understanding of risk assessment and future design of environmental benign BFRs.

Effect of ligand binding on the dynamics of trypsin. Comparison of different approaches

The intramolecular signal transduction induced by the binding of ligands to trypsin was investigated by molecular dynamics simulations. Ligand binding changes the residue-residue interaction energies and suppresses the mobility of loops that are in direct contact with the ligand. The reduced mobility of these loops results in the altered flexibility of the nearby loops and thereby transmits the information from ligand binding site to the remote sites. The analysis of the flexibility of all residues confirmed the coupling between loops L1 (185-188) and L2 (221-224) and the residues in the active center. The significance of S1 pocket residues for the signal transduction from the active center to the substrate-binding site was confirmed by the dynamical network and covariance matrix analyses. Gaussian network model and principal component analysis demonstrated that the active center residues had zero amplitude in the slowest fluctuations acting as hinges or anchors. Overall, our results provide a new insight into protein-ligand interactions and show how the allosteric signaling may occur.

Biasing conformational ensembles towards bioactive-like conformers for ligand-based drug design

IMPORTANCE OF THE FIELD

In silico or virtual screening has become a common practice in contemporary computer-aided drug discovery efforts and currently constitutes a reasonably mature paradigm. Application of ligand-based approaches to virtual screening requires the ability to identify the bioactive conformers of drug-like compounds as these conformers are expected to elicit the biological activity. However, given the complexity of the energy potential surfaces of such ligands and in particular those exhibiting some degree of flexibility and the limitation of contemporary energy functions, this is not an easy task.

AREAS COVERED IN THIS REVIEW

The current contribution provides an in-depth review of recent developments in the field of generating conformational ensembles of drug-like compounds with a particular emphasis of focusing such ensembles on bioactive conformers using both energy and structural criteria. The literature reviewed in this manuscript roughly covers the last decade.

WHAT THE READER WILL GAIN

Readers of this review will gain an appreciation for the complexity of identifying bioactive conformers of drug-like compounds and an exposure to the different computational methods which were developed in order to tackle this problem as well as to the remaining challenges in this field.

TAKE HOME MESSAGE

The identification of ensembles of bioactive conformers of drug-like compounds is far from being a solved problem. Recent research has advanced the field to the point where bioactive conformers could be readily identified from within conformational ensembles generated by contemporary computational tools. However, as such conformers are inevitably accompanied by many other non-relevant conformations, a focusing mechanism is required. New methods in this field are showing promise but more work is clearly needed. New research lines are proposed which are believed to enhance the performances and with it the usefulness of 3D ligand-based methods in drug discovery and development.

Locating binding poses in protein-ligand systems using reconnaissance metadynamics

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin-benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations.

Exploration of conformational transition in the aryl-binding site of human FXa using molecular dynamics simulations

Human coagulation Factor X (FX), a member of the vitamin K-dependent serine protease family, is a crucial component of the human coagulation cascade. Activated FX (FXa) participates in forming the prothrombinase complex on activated platelets to convert prothrombin to thrombin in coagulation reactions. In the current study, 30-ns MD simulations were performed on both the open and closed states of human FXa. Root mean squares (RMS) fluctuations showed that structural fluctuations concentrated on the loop regions of FXa, and the presence of a ligand in the closed system resulted in larger fluctuations of the gating residues. The open system had a gating distance from 9.23 to 11.33 Å, i.e., significantly larger than that of the closed system (4.69-6.35 Å), which allows diversified substrates of variable size to enter. Although the solvent accessible surface areas (SASA) of FXa remained the same in both systems, the open system generally had a larger total SASA or hydrophobic SASA (or both) for residues surrounding the S4 pocket. Additionally, more hydrogen bonds were formed in the closed state than in the open state of FXa, which is believed to play a significant role in maintaining the closed confirmation of the aryl-binding site. Based on the results of MD simulations, we propose that an induced-fit mechanism governs the functioning of human coagulation FX, which helps provide a better understanding of the interactions between FXa and its substrate, and the mechanism of the conformational changes involved in human coagulation.

Complete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations

The understanding of protein-ligand binding is of critical importance for biomedical research, yet the process itself has been very difficult to study because of its intrinsically dynamic character. Here, we have been able to quantitatively reconstruct the complete binding process of the enzyme-inhibitor complex trypsin-benzamidine by performing 495 molecular dynamics simulations of free ligand binding of 100 ns each, 187 of which produced binding events with an rmsd less than 2 Å compared to the crystal structure. The binding paths obtained are able to capture the kinetic pathway of the inhibitor diffusing from solvent (S0) to the bound (S4) state passing through two metastable intermediate states S2 and S3. Rather than directly entering the binding pocket the inhibitor appears to roll on the surface of the protein in its transition between S3 and the final binding pocket, whereas the transition between S2 and the bound pose requires rediffusion to S3. An estimation of the standard free energy of binding gives ΔG° = -5.2 ± 0.4 kcal/mol (cf. the experimental value -6.2 kcal/mol), and a two-states kinetic model k(on) = (1.5 ± 0.2) × 10(8) M(-1) s(-1) and k(off) = (9.5 ± 3.3) × 10(4) s(-1) for unbound to bound transitions. The ability to reconstruct by simple diffusion the binding pathway of an enzyme-inhibitor binding process demonstrates the predictive power of unconventional high-throughput molecular simulations. Moreover, the methodology is directly applicable to other molecular systems and thus of general interest in biomedical and pharmaceutical research.

Stabilizing of a globular protein by a highly complex water network: a molecular dynamics simulation study on factor Xa

The role of water molecules is increasingly attracting attention in structural biology, and many studies have demonstrated their crucial contribution to the stability and function of proteins. Here, we present molecular dynamics studies on factor Xa (fXa) to investigate the effect of water molecules in this serine protease. fXa is a key enzyme in the blood coagulation cascade, and thus, an important target for antithrombotic drugs. A reasonable representation of the structure is crucial for an investigation at the molecular level and, thus, a prerequisite for structure-based drug design. Simulations of well-resolved fXa X-ray structures with different sets of water molecules show the importance of a well-determined water set for the simulation. We discuss implications of different water sets on the structure and dynamics of fXa.

Binding and inactivation mechanism of a humanized fatty acid amide hydrolase by alpha-ketoheterocycle inhibitors revealed from cocrystal structures

The cocrystal X-ray structures of two isomeric alpha-ketooxazole inhibitors (1 (OL-135) and 2) bound to fatty acid amide hydrolase (FAAH), a key enzymatic regulator of endocannabinoid signaling, are disclosed. The active site catalytic Ser241 is covalently bound to the inhibitors' electrophilic carbonyl groups, providing the first structures of FAAH bound to an inhibitor as a deprotonated hemiketal mimicking the enzymatic tetrahedral intermediate. The work also offers a detailed view of the oxyanion hole and an exceptional "in-action" depiction of the unusual Ser-Ser-Lys catalytic triad. These structures capture the first picture of inhibitors that span the active site into the cytosolic port providing new insights that help to explain FAAH's interaction with substrate leaving groups and their role in modulating inhibitor potency and selectivity. The role for the activating central heterocycle is clearly defined and distinguished from that observed in prior applications with serine proteases, reconciling the large electronic effect of attached substituents found unique to this class of inhibitors with FAAH. Additional striking active site flexibility is seen upon binding of the inhibitors, providing insights into the existence of a now well-defined membrane access channel with the disappearance of a spatially independent portion of the acyl chain-binding pocket. Finally, comparison of the structures of OL-135 (1) and its isomer 2 indicates that they bind identically to FAAH, albeit with reversed orientations of the central activating heterocycle, revealing that the terminal 2-pyridyl substituent and the acyl chain phenyl group provide key anchoring interactions and confirming the distinguishing role of the activating oxazole.

Conformational variability of benzamidinium-based inhibitors

Determining the structure of a small molecule bound to a biological receptor (e.g., a protein implicated in a disease state) is a necessary step in structure-based drug design. The preferred conformation of a small molecule can change when bound to a protein, and a detailed knowledge of the preferred conformation(s) of a bound ligand can help in optimizing the affinity of a molecule for its receptor. However, the quality of a protein/ligand complex determined using X-ray crystallography is dependent on the size of the protein, the crystal quality, and the realized resolution. The energy restraints used in traditional X-ray refinement procedures typically use "reduced" (i.e., neglect of electrostatics and dispersion interactions) Engh and Huber force field models that, while quite suitable for modeling proteins, often are less suitable for small molecule structures due to a lack of validated parameters. Through the use of ab initio QM/MM-based X-ray refinement procedures, this shortcoming can be overcome especially in the active site or binding site of a small-molecule inhibitor. Herein, we demonstrate that ab initio QM/MM refinement of an inhibitor/protein complex provides insights into the binding of small molecules beyond what is available using more traditional refinement protocols. In particular, QM/MM refinement studies of benzamidinium derivatives show variable conformational preferences depending on the refinement protocol used and the nature of the active-site region.

Protonation changes upon ligand binding to trypsin and thrombin: structural interpretation based on pK(a) calculations and ITC experiments

The protonation states of a protein and a ligand can be altered upon complex formation. Such changes can be detected experimentally by isothermal titration calorimetry (ITC). For a series of ligands binding to the serine proteases trypsin and thrombin, we previously performed an extensive ITC and crystallographic study and were able to identify protonation changes for four complexes. However, since ITC measures only the overall proton exchange, it does not provide structural insights into the functional groups involved in the proton transfer. Using Poisson-Boltzmann calculations based on our recently developed PEOE_PB charges, we compute pK(a) values for all complexes of our former study in order to reveal the residues with altered protonation states. The results indicate that His57, a member of the catalytic triad, is responsible for the most relevant pK(a) shifts leading to the experimentally detected protonation changes. This finding is in contrast to our previous assumption that the observed protonation changes occur at the carboxylic group of the ligands. The newly detected proton acceptor is used for a revised factorization of the ITC data, which is necessary whenever the protonation inventory changes upon complexation. The pK(a) values of complexes showing no protonation change in the ITC experiment are reliably predicted in most cases, whereas predictions of strongly coupled systems remain problematic.

Calculation of absolute protein-ligand binding affinity using path and endpoint approaches

A comparative analysis is provided of rigorous and approximate methods for calculating absolute binding affinities of two protein-ligand complexes: the FKBP protein bound with small molecules 4-hydroxy-2-butanone and FK506. Our rigorous approach is an umbrella sampling technique where a potential of mean force is determined by pulling the ligand out of the protein active site over several simulation windows. The results of this approach agree well with experimentally observed binding affinities. Also assessed is a commonly used approximate endpoint approach, which separately estimates enthalpy, solvation free energy, and entropy. We show that this endpoint approach has numerous variations, all of which are prone to critical shortcomings. For example, conventional harmonic and quasiharmonic entropy estimation procedures produce disparate results for the relatively simple protein-ligand systems studied in this work.